Shin, Hyeon-ShicSchonfeld, PaulLee, Young-Jae2020-05-152020-05-152019-12http://hdl.handle.net/11603/18644Limited access to fresh food sources--ones within reasonable distances with reliable, affordable transportation--has become a public health concern. The negative associations between a lack of fresh food consumption and health are well known. Because certain demographic groups are disproportionately affected by the absence of stores selling healthy and affordable food, equity issues result. Many inner-city residents are left in neighborhoods devoid of such stores, and every day they are forced to trade off increased costs against healthy food consumption and health. This study aimed to develop a cost-effective last-mile fresh food delivery system to households in food deserts, which could help improve fresh food accessibility. Six alternative delivery modes--conventional trucks, e-bikes, shared-ride transit, parcel lockers, pop-up stores, and independently contracted drivers--were identified and optimized by employing Traveling Salesman Problem. Then we compared the results with the system's total costs. Sensitive analyses were conducted in terms of the time of delivery, zone size, user's value of time waiting for goods, the optimal number of lockers, costs associated with combined deliveries at lockers as well as customer addresses, and a second delivery attempt. Building on optimized modes, GIS network analyses were performed for randomly selected household locations in parts of poverty-prone West Baltimore. Numerical results showed that deliveries by trucks are the most cost-effective alternative, while the third-party deliveries ranked second. The two most expensive alternatives were shared-ride service and e-bike deliveries, based on the estimated costs of providing them.Public Domain Mark 1.0http://creativecommons.org/publicdomain/mark/1.0/Food deserts, network optimization, network analysis, delivery systemText